Statistical schema matching across web query interfaces

By Bin He, Kevin Chen-Chuan Chang. ACM SIGMOD Conference, 2003

380 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/3b76b68c44e4d9f875e2aaa95eae689bbc67396c

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In Artificial Intelligence

In Information Systems

In Management Science and Operations Research

Citations in the corpus

Ontology Matching (2007, background): “− Based on the work in (He and Chang 2003), the authors assume the existence and availability of a populated global schema, that is a view capturing common attributes of data, for web databases of the same domain of interest.”
Corpus-based schema matching (2005, background): “The intuition for this is that the same concept is never duplicated within one schema (similar to [8, 26]).”
An interactive clustering-based approach to integrating source query interfaces on the deep Web (2004, methodology): “Schema and Interface Matching: There is a large body of works on schema matching and integration [6, 7, 9, 10, 11, 14, 16, 18, 19, 23, 29].”
Automatically refining the wikipedia infobox ontology (2008, background): “He and Chang proposed a statistical schema mapping framework across Web query interfaces by integrating l ar e numbers of data sources on the Internet [18].”
Data integration: the teenage years (2006, background): “Hence, a significant branch of the research community focused on semi-automatically generating schema mappings [12, 21, 31, 32, 33, 56, 63, 75, 76, 82, 84, 88, 89, 96, 110].”
Structured databases on the web: observations and implications (2004, background): “Second, for query-schema matching, as [17, 18] reported, the observation of converging attributes leads us to hypothesize a hidden generative behavior, which probabilistically generates, from a finite vocabulary, the schemas we observed– Such generative behavior explains the regularity observed.”
InfoGather: entity augmentation and attribute discovery by holistic matching with web tables (2012, background): “He and Chang proposed holistic matching of schemas associated with deep web query interfaces [12].”
RiMOM: A Dynamic Multistrategy Ontology Alignment Framework (2009, background): “ONTOLOGY, as the means to conceptualize domain knowl-edge, has become the enabler of the fulfillment of the Semantic Web vision.”
iMAP: discovering complex semantic matches between database schemas (2004, background): “They do not consider the important class of more complex matches, such as address = concat(city,state) and room-price = room-rate * (1 + tax-rate).”